Receiving station with interference signal suppression

ABSTRACT

An optimum combiner that reduces the amount of interference imposed upon a first base station by transmissions of other base stations within the same communication system. Two antennas are used to receive transmissions within a receiving station. A rake receiver is coupled to each antenna. By optimally combining the signals that are received by each independent finger of the rake receiver, interference that is correlated between a finger associated with the first antenna and a finger associated with the second antenna can be minimized with respect to the desired signal. Optimum combining requires determination of optimum combining coefficients.

CROSSREFERENCE

This application for patent is a continuation of U.S. patent applicationSer. No. 09/332,857 filed Jun. 14, 1999, entitled “RECEIVING STATIONWITH INTERFACE SIGNAL SUPPRESSION,” by Mario Bonaccorso, et al., nowU.S. Pat. No. 6,285,861, issued on Sep. 4, 2001.

This application for patent is related to U.S. patent application Ser.No. 09/414,125 filed Oct. 8, 1999, entitled “SELECTION MECHANISM FORSIGNAL COMBINING METHODS,” by Fuyun Ling, assigned to the assigneehereof, now U.S. Pat. No. 6,466,558, issued on Oct. 15, 2002.

RELATED FIELD

This disclosed method and apparatus relates to wireless communicationssystems, and more specifically to suppressing interference.

BACKGROUND

In a conventional wireless communications system, a mobile station(cellular telephone, portable computer, etc.) is served by a network ofbase stations. Such base stations serve as the communication relaystation for mobile stations. Accordingly, a mobile station must be inwireless communication with at least one base station whenever themobile station is turned on in order to communicate with the othercomponents of a communications system. Mobile stations sometimes moveout of a region served by one base station and into a region served byanother base station. Base stations note this fact, and “hand-off”communication from the first base station to the second. It is commonfor a mobile station to be in communication with both the first andsecond base station for periods of time. A mobile station that is incommunication with more than one base station is said to be in “softhandoff.” In some cases, a mobile station will be in soft handoff withmore than two base stations at any one time.

Soft handoff is desirable because it reduces dropped calls. In addition,soft handoff allows the mobile unit to receive the same information frommore than one source and to use all of this received information (orenergy) to assist in decoding the information that is being transmittedto the mobile station by each base station. Using informationtransmitted from more than one base station means that the power levelthat is required from any one base station is reduced.

One type of wireless communication system is known as Code DivisionMultiple Access (CDMA). CDMA systems offer greater capacity than othersystems. That is, the number of channels of information that can becommunicated concurrently is greater in CDMA systems than in othersystems, such as a time division multiple access (TDMA) system or afrequency division multiple access (FDMA) system.

In CDMA systems in which both voice and data are being communicated,base stations transmit to as many mobile stations as are in the coveragearea for that base station on the same frequency at the same time. Inaddition, each such base station transmits at the same frequency asevery other base station in the network. Signals transmitted to aparticular mobile station are distinguishable from signals transmittedto other mobile stations only by the fact that they are transmittedusing different codes. In contrast, in a TDMA system, transmissions to afirst mobile station are sent during a first period of time andtransmissions to a second mobile station are sent during a second,non-overlapping period of time. In an FDMA system, transmissions to afirst mobile station are transmitted on a first frequency andtransmissions to a second mobile station are transmitted on a secondfrequency. Because a CDMA receiver can receive more than one channel ata time while tuned a single frequency, a CDMA receiver can moreconveniently perform soft handoff then can a TDMA receiver or an FDMAreceiver.

While CDMA systems have the advantage of being ideally suited for softhandoff, signals transmitted to a first mobile station using a firstcode appear as noise to a second mobile station attempting to receivesignals transmitted to the second mobile station using a second code.This interference is preferably minimized by making the codes assignedto signals transmitted from a base station orthogonal with codesassigned to all other signals being transmitted by that base station.However, codes used with signals that are transmitted by a first basestation can not be made orthogonal with codes used with signalstransmitted by a second base station. Therefore, base stations carefullyregulate the amount of power used to transmit signals to mobilestations. The power must be high enough to get the signal through, butthe power is preferably no higher than necessary, since additional powerappears to other mobile stations as additional interference and reducesthe number of mobile stations that can be served.

Because conventional CDMA communication systems must handle both voiceand data, certain performance requirements must be met. One suchrequirement is that the delay between the time the information istransmitted from one end of the communication system until the time theinformation is received at the other end of the communication systemmust be relatively short. That is, when two people are talking, anyperceptible delay between the time words are spoken at one end of theline and the time those words are heard at the other end of the linewould be annoying to both the speaker and the listener.

In contrast, many data communication systems can tolerate relativelylong delays between the time information is sent and that information isreceived. CDMA systems have recently been proposed that take advantageof the fact that relatively long delays can be tolerated in systemsdesigned to handle only data. Such systems are referred to herein ashigh data rate (HDR) systems. In HDR systems, a base station isdedicated to communicating with only one mobile station at any one time.The capacity advantages of CDMA are realized with HDR systems. However,it may be difficult or undesirable to perform soft handoff due to thefollowing reasons. First, the transmissions from a base station in anHDR system are all directed to one mobile station at any particulartime. Therefore, while the number of code channels being transmittedfrom an HDR base station is essentially the same, all of the codechannels are intended to be received by one mobile station at any onetime. As a result, it is complex to coordinate the times of transmissionbetween two base stations in order to allow soft handoff between the twobase stations. Second, in order to perform soft handoff, it is necessaryto distribute the same data between more than one base station. Thiswill greatly increase the amount of data to be transferred between basestations, especially for high data rate applications. Third, systemcapacity increases if the mobile unit can always connect to the bestserving base station instead of using soft handoff, assuming that thechannel condition is relatively static, as is likely for an HDR system.This is true, since an HDR base station typically transmits at maximumpower to allow the best data rate. That is, the rate at which data canbe transmitted is directly proportional to the amount of power received.Therefore, in order to maximize the data rate, the maximum power istransmitted. However, this increases the amount of interference a firstbase station contributes to the signals received by mobile stationsattempting to receive signals from a second base station.

Accordingly, there is a need for a method and apparatus for reducing theamount of interference that a first base station contributes to mobilestations attempting to receive signals from one or more other basestations.

SUMMARY OF THE PRESENTLY DISCLOSED METHOD AND APPARATUS

The presently disclosed method and apparatus reduces the amount ofinterference imposed upon a first base station by transmissions of otherbase stations within the same communication system. The presentlydisclosed method and apparatus takes into account the fact that softhandoff is not easily implemented or undesirable in some communicationsystems, such as a high data rate (HDR) communication system in whichmultiple code channels are being transmitted to one receiving station,such as a mobile station, at a time. That is, in a typical HDR system,each base station is transmitting to only one receiving station at atime. To coordinate the times of transmission and data transfer betweentwo base stations in order to allow soft handoff between two basestations is complex. Moreover, the capacity of the HDR system mayincrease by not using soft handoff under typical channel conditions.Therefore, the presently disclosed method and apparatus deviates fromthe traditional approach of performing soft handoff and relies ontechniques that use two or more antennas for decreasing the interferencebetween transmissions from a first base station and transmissions fromone or more other base stations.

In accordance with the presently disclosed method and apparatus, twoantennas are used to receive transmissions within a receiving station. Arake receiver is coupled to each antenna. The rake receiver has aplurality of fingers, each finger having the ability to identify andindependently decode signals arriving with different propagation delays(i.e., the delay encountered between the time the signal is transmittedand the time the signal is received). By optimally combining the signalsthat are received by each independent finger of the rake receiver,interference that is correlated between a finger associated with thefirst antenna and a finger associated with the second antenna can beminimized with respect to the desired signal. Optimum combining requiresdetermination of optimum combining coefficients as follows.

Optimum combining coefficients for each of the signals received by thefingers of the rake receiver are determined by first pairing the outputfrom a first finger associated with the first antenna with the outputfrom a second finger associated with the second antenna. The firstfinger receives the desired signal with essentially the same propagationdelay as the second finger. That is, the path of the signal decoded bythe first finger and the path of the signal decoded by the second fingerdiffer only because the first finger is associated with the firstantenna and the second finger is associated with the second antenna. Anautocorrelation matrix is estimated. In one of the presently disclosedmethods and apparatus, the autocorrelation matrix is an estimate of theautocorrelation of the received signals. Alternatively, theautocorrelation matrix is an estimate of the autocorrelation of thereceived noise plus interference.

In addition, the cross-correlation between the received signal and thetransmitted symbol is estimated by estimating the elements of a fadingcoefficient vector. Each element of the fading coefficient vector is afading coefficient associated with one of the signal paths traversed bythe signals received by the rake receiver. The fading coefficient vectoris preferably estimated based on the pilot bursts received on eachfinger.

The autocorrelation matrix of the noise plus the interference isestimated from the received noise component of each of the signalsreceived by the fingers of the rake receiver. The received noisecomponent for a particular finger is calculated by subtracting thefading coefficient associated with the signal received by that fingerfrom the total signal received by that finger in the pilot bursts. Inanother of the presently disclosed methods and apparatus, the noise andinterference is estimated by subtracting the signal y(m) from the signaly(m+1) one chip later in time (i.e., subtracting adjacent samples). Inyet another of the presently disclosed methods and apparatus, theautocorrelation matrix of the noise plus interference R_(nn) isestimated by subtracting the fading coefficient vector multiplied by thetranspose conjugate of the fading coefficient vector, from theautocorrelation matrix R_(yy) of the received signal y(m).

Once the fading coefficient vector and the autocorrelation matrix of thesignal received by each pair of fingers has been calculated, thesevalues are used to calculate the optimum combining coefficients.Alternatively, once the fading coefficient vectors and theautocorrelation matrix of the noise plus interference for each pair offingers have been calculated, they are used to calculate the optimumcombining coefficients.

Upon combining the signals received by each finger of the rake receiverusing the optimum combining coefficients, it is desirable to calculatethe signal to interference plus noise ratio of the output from theoptimum combiner. This ratio is calculated using the transpose conjugateof the optimum combining coefficients and the fading coefficient vector.The result is a system in which interference from sources other than thesource of the desired signal is suppressed with respect to the desiredsignal to improve decoding. The resulting signal to noise plusinterference is calculated to allow a receiving station so equipped todetermine the data rate that the channel can support.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic drawing of a wireless network according to thepresently disclosed method and apparatus.

FIGS. 2A and 2B taken together are a simplified block diagram of areceiving station of the presently disclosed method and apparatus.

FIG. 3 is a simplified block diagram of one optimum combiner of one ofthe presently disclosed methods and apparatus.

FIG. 4A is a functional block diagram of a combiner coefficientprocessor of one of the presently disclosed methods and apparatus.

FIG. 4B is a functional block diagram of a combiner coefficientprocessor 224′ of an alternative method and apparatus.

FIG. 5 is an illustration of a data field for which three consecutivefading coefficient estimates are to be averaged and then interpolatingbetween consecutive averages.

FIG. 6A is a functional block diagram of a combiner coefficientprocessor 600 of an alternative method and apparatus.

FIG. 6B is a functional block diagram of a combiner coefficientprocessor 600′ in yet another alternative method and apparatus.

DETAILED DESCRIPTION

FIG. 1 is a schematic drawing of a wireless network 100 according to thepresently disclosed method and apparatus. In one of the presentlydisclosed methods and apparatus, the wireless network 100 is a codedivision multiple access (CDMA) high data rate (HDR) system. A firstbase station 102 has an antenna 104. The first base station 102transmits signals that are intended to be received by a receivingstation 110, such as a mobile station, having two antennas 112, 114. Thesignals that are transmitted by the first base station 102 are shown totraverse two distinct paths from the first base station 102 to the twoantennas 112, 114 of the receiving station 110. Accordingly, fourdesired signals (y₁₁, y₁₂, y₂₁, y₂₂) are received at the receivingstation 110 from the base station 102. Each desired signal is delayed adifferent amount (i.e., has a different propagation delay) due to thedifferent paths traversed. The first subscript associated with a desiredsignal is indicative of the antenna that received the signal. The secondsubscript associated with a desired signal is indicative of thepropagation delay encountered by the signal.

It should be noted that while y₁₁, y₂₁ do not traverse exactly the samepath (i.e., they are received by different antennas as indicated by thefirst subscript) their delays are essentially equal when contrastedagainst the delays of y₁₂ and y₂₂. That is, the difference in thepropagation delay between the signals y₁₁ and y₂₁ will be far less thanthe difference in the propagation delay between the signal y₁₁ andeither y₁₂, or y₂₂, since the paths traversed by signals y₁₂ and y₂₂ arefar longer than the path traversed by signal y₁₁. Likewise, thedifference in the propagation delay between the signals y₁₂ and y₂₂ willbe far less than the difference in the propagation delay between thesignal y₁₂ and either y₂₁, or y₁₁, since the path traversed by signalsy₂₁ and y₁₁ is far shorter than the path traversed by the signal y₁₂.

A second signal source also transmits signals being received by thereceiving station 110. For simplicity, the second signal source isdescribed throughout this document as a second base station 108 havingan antenna 106. However, it will be understood by those skilled in theart that the second signal source may be a second antenna associatedwith the same or another base station, or different portion of the sameantenna transmitting from the same base station. However, the signalsbeing transmitted by the second base station 108 are not intended to bereceived by the receiving station 110. The base stations 102 and 108each transmit broadband signals over the same frequency band. Therefore,the signals that are being received by the receiving station 110 fromthe second base station 108 interfere with the reception by thereceiving station 110 of the signals transmitted from the first basestation 102.

For ease of understanding, only two base stations 102, 108 are shown.However, it will be clear to those skilled in the art that more than twobase stations may be transmitting. Furthermore, the receiving station110 is shown to have only two antennas 112, 114. However, in one of thepresently disclosed methods and apparatus, additional antennas may beprovided on the receiving station 110.

In the presently disclosed method and apparatus, the receiving station110 uses the signals received by the two antennas 112, 114 to assist insuppressing interference from signal sources that are transmitted fromdifferent antennas, or portions of an antenna, than the desired signal.

FIGS. 2A and 2B taken together are a simplified block diagram of areceiving station 110 of the presently disclosed method and apparatus.As noted above, incoming signals are received at the receiving station110 over each of the two antennas 112, 114. The receiving station 110preferably includes two receiver modules 201A, 201B. Each receivermodule 201 includes: a radio frequency/intermediate frequency (RF/IF)converter 200, 202; an analog to digital (A/D) converter 204, 206; arake receiver 208, 210, a pilot/data demultiplexer (demux) 212, 214; anda plurality of Walsh decover modules 216A, 216B, 216C, 216D, 216E, 216F.

Each of the two RF/IF converters 200, 202 is coupled to an associatedone of the two antennas 112, 114. Accordingly, signals received overeach of the two antennas 112, 114 are coupled to the corresponding radioRF/IF converters 200, 202.

Each RF/IF converter 200, 202 is coupled to a corresponding one of twoA/D converters 204, 206. The A/D converters 204, 206 convert the outputfrom the RF/IF converter 200, 202 into a digital form. Alternatively, asingle A/D converter may be used to convert the received analog signalsfrom both antennas to digital form. Each A/D converter 204, 206 iscoupled to a corresponding one of two rake receivers 208, 210.

Each rake receiver 208, 210 is capable of distinguishing between each ofthe signals that have originated from a desired source base station andthat encounter different propagation delays to get to the receivingstation 110. Rake receivers used in CDMA receivers are well known in theart for receiving and discriminating between CDMA signals. Since signalsy₁₁, y₁₂, y₂₁, y₂₂ encounter different delays, a conventional rakereceiver is capable of distinguishing between these signals. Each signaly₁₁, y₁₂, y₂₁, y₂₂ from the desired source (i.e., the base station 102)that has a distinguishable delay is assigned to a unique “finger” 213A,213B, 213C, 213D, 213E, 213F of the rake receiver 208, 210. Each suchfinger 213 outputs a signal that is despread with a delayedpseudo-random noise (PN) code generated by a PN generator 211. The PNcode output from the generator 211 is delayed by one of a plurality ofdelay modules 209A, 209B, 209C, 209D, 209E, 209F. The amount of thedelay imposed by each delay module 209 is set such that the PN codeoutput from each delay module 209 is synchronized to the PN code withwhich the signals received from the desired source base station 102 wereoriginally spread, plus the propagation delay encountered intransmission from the base station 102 to the receiving station 110.

It should be noted that the signals transmitted by each base station102, 108 may be spread (i.e., encoded) with the same PN code. However, asubstantially different delay is imposed with respect to the start ofthe PN sequence used to encode the signals from each base station 102,108. The difference in the delay is substantially greater than the delaybetween any two signals that would arrive at the receiving station 110from the same base station 102 over different paths. Therefore, byspreading signals transmitted from different base stations with the samePN code, but with substantially different delays, signals from a firstbase station 102 can be distinguished from signals from a second basestation 108. Furthermore, signals transmitted from the first basestation 102 to the receiving station 110 have a different propagationdelay than signals transmitted from the base station 108 to thereceiving station 110. Accordingly, these signals can be distinguishedfrom one another. It should be noted that none of the delay modules 209are set to promote reception of the signals transmitted by the secondbase station 108.

In a base station generating signals to be received by one of thepresently disclosed methods and apparatus, a pilot signal is timemultiplexed with data. In one such base station 102, the pilot and eachdata stream are covered (i.e., encoded) with a different Walsh code. Thepilot is preferably covered with the Walsh code that has a constantvalue, making decovering the pilot channel less difficult. During thetime when the pilot channel is being transmitted (i.e., the pilotburst), no data is transmitted. Two such pilot bursts occur in eachforward link slot. A forward link slot is a predetermined period of timewithin the signal transmitted from a base station to a receivingstation. During the time (i.e., the data field) when the data is beingtransmitted, the pilot channel is not transmitted. The data is codemultiplexed. That is, the data is divided into separate data streams.Each data stream is covered with a different Walsh code. All of the datastreams are then transmitted at the same time. For example, a firstportion of the data is covered with a first Walsh code, a second portionof data is covered with a second Walsh code, and a third portion of datais covered with a third Walsh code. The first, second, and thirdportions are then all transmitted by the base station at the same timeduring the data field.

Since the data and pilot are transmitted in time multiplexed format, inone of the presently disclosed methods and apparatus, the receivingstation 110 includes one pilot/data demux 212, 214 associated with eachof the antennas 112, 114. However, a single demux may be provided fordemultiplexing the signals received by both of the antennas 112, 114.The output from the first demux 212 is a plurality of pilot streamsy_(p11)(m), y_(p12)(m), . . . y_(p1N)(m) and a plurality of data streamsy_(d11)(m), y_(d12)(m), . . . y_(d1N)(m), where y_(p11)(m) indicates aseries of pilot samples, each taken at a time “mT” over the pilotchannel received on antenna 1, with propagation delay 1, and wherey_(d11)(m) indicates a series of data samples, each taken at a time “mT”over the data channel received on antenna 1, delay 1, and where “m” isan integer and “T” is a time equal to one data chip in duration.

Each pilot and data stream having the same numeric subscripts isassociated with the same finger 213 of the rake receiver 208, 210. Eachdata stream is coupled to Walsh decover module 216A, 216B, 216C, 216D,216E, 216F. Each Walsh decover module 216 separates the code channelsthat were code multiplexed into the data field prior to transmissionfrom the base station 102. The output from the Walsh decover modules216A, 216B, 216C, 216D, 216E, 216F are separate data streams that havebeen decovered, as is well known to those skilled in the art. Thesepilot and data signals are then coupled to an optimum combiningprocessor 218.

The optimum combining processor 218 shown in FIG. 2B includes threeoptimum combiners 220A, 220B, 220C and a combiner coefficient processor224. It should be noted that each optimum combiner 220 is associatedwith a corresponding one code channel (i.e., Walsh code used to coverthe data transmitted over that code channel). That is, if each the Walshdecover module 216 puts out three data streams (each associated with adifferent code channel and having been decovered by a different Walshcode), then there will be three optimum combiners 220 that will be used.However, it should be understood that in an alternative method andapparatus, the number of code channels and optimum combiners 220 maydiffer from the three shown in FIG. 2B. Furthermore, it should be notedthat a single module can perform the functions of more than one optimumcombiner. Each optimum combiner 220 is coupled to all of the Walshdecover modules 216, providing each optimum combiner 220 with the datatransmitted on one code channel via multiple paths received over bothantennas. The output from each optimum combiner 220 is a stream of datasymbols representing the data that modulates the signals transmitted bythe base station 102. Due to the processing by the optimum combiningprocessor 218, the interference encountered when decoding the symbols isless than would result from a conventional combining of the input to theoptimum combiner 220. That is, the SINR of the signals modulated withthe output symbols is greater than the SINR of any of the data streamsinput to the optimum combiner 220. Furthermore, the SINR of the outputsymbols is greater than would result from a conventional combining ofthe inputs to the optimum combiner 220.

FIG. 3 is a simplified block diagram of one optimum combiner 220A in oneof the presently disclosed methods and apparatus. Since each optimumcombiner 220 is essentially identical, only one such optimum combiner220A will be described. The optimum combiner 220A includes a pluralityof two input multiplication modules 302. The multiplication modules 302multiply the signal at the first input with the signal at the secondinput and provide the product at the output of the multiplication module302. It should be noted that the multiplication modules 302 may beimplemented as a function performed by a programmable device (such as ageneral purpose processor or a DSP) or as dedicated hardware orprogrammable logic, or in any other manner that allows themultiplication function to be carried out (such as circuitry orprocessing functionality within an application specific integratedcircuit (ASIC)).

The number of multiplication modules 302 in an optimum combiner 220 ispreferably equal to the total number of Walsh decover modules 216 in thereceiving station 110. A first input to each multiplication module 302is coupled to a unique corresponding one of the Walsh decover modules216. Accordingly, each data stream received on the one code channelassociated with the optimum combiner 220A is coupled to a first input ofthe particular two input multiplication module 302 a that is associatedwith that Walsh decover module 216A. In the method and apparatus shownin FIG. 2, there are six decover modules 216A, 216B, 216C, 216D, 216E,216F. Accordingly, six multiplication modules 302A, 302B, 302C, 302D,302E, 302F are shown in the optimum combiner 220A of FIG. 3. A secondinput to each multiplication module 302 is coupled to the combinercoefficient processor 224 by signal line 223. The combiner coefficientprocessor 224 calculates optimum combining coefficients (w_(ij)*(m)).The subscript “i” represents the particular antenna associated with afinger 213 and the subscript “j” represents the particular delayencountered by a signal transmitted from a desired source. As notedabove, while the paths traversed by signals received by the two antennas112, 114 (such as signals y₁₁ and y₂₁ shown in FIG. 1) are not identicaldue to the fact that the signals are received by different antennas, thesame second subscript is used to denote that these signals haveencountered essentially equal propagation delays. Similarly, the secondsubscript of the optimum combining coefficients indicates whichpropagation delay was encountered by the signal to be multiplied withthat optimum combining coefficient.

The multiplication performed by the multiplication modules 302 allowseach received signal to be weighted and rotated (i.e., the phase andamplitude of the received signals can be adjusted). By rotating thephase, the signal to interference plus noise ratio (SINR) of thecombined signal output from the summing module 304 is optimized. Thatis, the SINR will be the highest possible. Accordingly, the interferencecaused by undesired signals will be reduced. That is, the power receivedfrom a base station 102 attempting to communicate with the receivingstation 110 can be maximized with respect to the power received from abase station 108 that is not attempting to communicate with thereceiving station 110.

The combiner coefficient processor 224 (shown in FIG. 2b) is coupled tothe second input of each multiplication module 302 by signal lines 223.It should be noted that to reduce the number of lines in FIG. 2B, asingle signal line 223 is shown from the combiner coefficient processor224 to each optimum combiner 220. However, this line 223 represent aconnection over which a plurality of values of wij*(m) (six in the caseshown in FIGS. 2b and 3) are provided to each multiplication module 302in each optimum combiner 220. These values allow the multiplicationmodules 302 to optimally adjust the received signals before combiningwithin a summing module 304. The summing module 304 sums the products tocombine each of the received rotated signals. Accordingly, the optimumcombiner 220A performs a dot product operation. The output of thesumming module 304 (i.e., the output from the optimum combiner 220A) isprovided as an input sample to a conventional decoding or detectionmodule or a processor that performs conventional decoding or detectionfunctions, such as the error correcting decoder 226. The output from thesumming module 304 can be expressed as:

{tilde over (y)}(m)=w ^(H)(m)·y(m)  (1)

where H denotes the transpose conjugate; y(m)=[y₁₁(m),y₁₂(m), . . .y_(ij)(m), . . . ]^(T) is the vector containing the sampled receivedsignal at each rake finger 213 associated with each antenna 112, 114 attime mT after Walsh decover; y_(i,j) is the received signal in thej^(th) rake finger 213 coupled to the i^(th) antenna at time mT afterWalsh decover; w(m)=[w₁₁(m),w₁₂(m), . . . w_(ij)(m). . . ]^(T) is thevector containing the optimum combining coefficients at time mT.

It should be noted that j^(th) rake finger associated with the firstantenna will have the same delay as the j^(th) rake finger associatedwith the second antenna. For example, the delay imposed by the delaymodule 209B associated with the 2^(nd) rake finger 213B which receivessignals from the first antenna 112 will be the same as the delay imposedby the delay module 213E associated with the 2^(nd) rake finger 213Ewhich receives signals from the second antenna 114. Accordingly, in thepresently disclosed method and apparatus, each delay module 209associated with the first antenna 112 preferably has a counter-partdelay module 209 associated with the second antenna 114. Each of themodules 209 of such a pair of counter-part delay modules 209 preferablyhas the same delay.

After Walsh decover, the received signal at the j^(th) rake finger 213of the i^(th) antenna can be represented as:

y _(ij)(m)=c _(ij)(m)·x(m)+n _(ij)(m)  (2)

where: x(m) is the transmitted symbol at time mT; c_(ij)(m) is thefading coefficient at time mT; and n_(ij)(m) is a complex numberrepresenting the thermal noise plus the interference at the j^(th) rakefinger 213 coupled to the i^(th) antenna at time mT. The fadingcoefficient c_(ij)(m) is a complex number representing instantaneouschannel gain, at a time “mT,” including the effect of propagation loss,shadowing, and fast fading. In binary phase-shift keying, the symbolx(m) is a value of either +1 or −1. However, in quadrature phase-shiftkeying, quadrature amplitude modulation, or other such modulationtechniques, the symbol x(m) belongs to a modulation constellation.

Generation of Optimum Combining Coefficients

The following is a detailed description of one disclosed method andapparatus used to determine optimum combining coefficients. FIG. 4A is afunctional block diagram of a combiner coefficient processor 224 of oneof the presently disclosed methods and apparatus. It should be notedthat each of the optimum combiners 220 operates the same. Therefore, forsimplicity, the operation of only one such optimum combiner 220 isdescribed.

Each of the functions being performed in the modules shown in FIG. 4Amay be performed by a programmable device (such as a general purposeprocessor or a DSP) or as dedicated hardware or programmable logic, orin any other manner that allows the function to be carried out (such ascircuitry or processing functionality within an application specificintegrated circuit (ASIC)). These functions may be performed by a singlemodule, or by multiple modules. Furthermore, each such module may bephysically integrated together with one or more of the other modules ormay be physically independent from one or more of the other modules.

The combiner coefficient processor 224 is coupled to the two pilot/datademultiplexers 212, 214. The pilot/data demultiplexer 212 provides thepilot signals y_(p1)(m) to the combiner coefficient processor 224, wherey_(p1)(m)=[y_(p11)(m), y_(p12)(m). . . y_(p1N)(m)]. The pilot/datademultiplexer 214 provides the pilot signals y_(p2)(m) to the combinercoefficient processor 224, where y_(p2)(m)=[y_(p21)(m), p_(p22)(m). . .y_(p2N)(m)].

In one of the presently disclosed methods and apparatus, the values ofthe optimum combining coefficients are calculated as a function of anautocorrelation matrix and the cross-correlation r_(yx)(m) of thereceived signal y(m) with the transmitted symbols x(m). In one of thepresently disclosed methods and apparatus, the autocorrelation matrix isan estimate of the autocorrelation of the received signal. Accordingly,the combiner coefficient processor 224 calculates the optimum combiningcoefficients as:

w(m)=R_(yy) ⁻¹(m)r_(yx)(m)  (3)

where: R_(yy)(m) is the autocorrelation matrix of the vectory(m)=[y₁₁(m),y₁₂(m), . . . y_(ij)(m), . . . ]^(T) containing the sampledreceived signal at each rake finger 213 coupled to each antenna at timemT after Walsh decover (i.e. R_(yy)(m)=E [y(m)·y^(H)(m)]); and r_(yx)(m)is the cross-correlation between the vector y(m) and the transmittedsymbol x(m) (i.e. r_(yx)=E [y(m)·x*(m)], where E denotes the expectationvalue as defined in statistical mathematics and x*(m) denotes thecomplex conjugate of x(m).

In an alternative method and apparatus, the values of the optimumcombining coefficients are calculated by a combiner coefficientprocessor 224′ (as shown in FIG. 4B and discussed in detail below) as:

w′(m)=R_(nn) ⁻¹(m)r_(yx)(m)   (4)

where R_(nn)(m) is the autocorrelation matrix of the thermal noise plusinterference vector n(m)=[n₁₁(m),n₁₂(m), . . . n_(ij)(m). . . ]^(T)(i.e. R_(nn)(m)=E [n(m)·n^(H)(m)]): and r_(yx)(m) is as defined above.In a system in which pilot symbols are represented by |x|=+1;

r_(yx)=E [y(m) x*(m)]=c=[c₁₁(m),c₁₂(m), . . . ,c_(ij)(m). . . ]^(T)  (4a)

where c_(ij)(m) is the fading coefficient at time mT.

The variable w as described in equation (3) and w′ as described inequation (4) only differ by a scalar factor. That is:

w′=(1+h)w   (5)

where: h=c^(H)R_(nn) ⁻¹c.

Estimation of the Cross-Correlation r_(yx)

The estimations of the cross-correlation r_(yx) between the receivedsignal y(m) and the transmitted symbol x(m) is determined from thefading coefficient vector c during the pilot bursts in the forward linkslot, since the cross-correlation r_(yx) is equal to the vectorc=[c₁₁,c₁₂, . . . c_(ij, . . .) ]^(T) of the fading coefficients, asdescribed above.

The estimation of c is performed by a fading coefficient estimationmodule 401 using the pilot bursts of the forward link slot as follows.The fading coefficient module 401 receives each of the pilot signalsy_(p11)(m), y_(p12)(m), . . . y_(p1N)(m), y_(p21)(m), y_(p22)(m), . . .y_(p2N)(m) output from each of the two pilot/data demultiplexers 212,214. For simplicity sake, FIG. 4A shows a vector y_(p)(m)=y_(p11)(m),y_(p12)(m), . . . y_(p1N)(m), y_(p21)(m), y_(p22)(m), . . . y_(p2N)(m).In one of the presently described methods and apparatus, the transmittedsymbol during the pilot burst is equal to a constant value of one (i.e.,x=1). Therefore, each element of the fading coefficient vector c_(ij)(m)can be estimated as: $\begin{matrix}{{\hat{c}}_{ij} = {\frac{1}{M}{\sum\limits_{m = 1}^{M}{y_{pij}(m)}}}} & (6)\end{matrix}$

where ĉ_(ij) is an estimate of the fading coefficient c_(ij)(m) for thepilot burst at the j^(th) rake finger of the i^(th) antenna, y_(pij)(m)is the m^(th) sample of the received signal in the pilot burst at thej^(th) rake finger of the i^(th) antenna, and M is the number of symbolsin the pilot burst.

The fading coefficient estimate ĉ_(ij) determined in equation (6) givesan estimate of the cross-correlation r_(yx), only in the pilot bursts.Therefore, in order to perform coherent detection and determine theoptimum combiner coefficients using equations (3), an estimate of thefading coefficient ĉ_(ij) in the data chips is calculated in a firstinterpolation module 403.

In one of the presently disclosed methods and apparatus, an estimate ofthe fading coefficient ĉ_(ij) in the data chips is made by the linearinterpolation module 403 by interpolation between the estimates of twofading coefficients ĉ_(ij) determined in consecutive pilot bursts.Alternatively, the estimate of the fading coefficient ĉ_(ij) in the datachips is made by averaging a plurality (e.g., two or three) of fadingcoefficients ĉ_(ij) in consecutive pilot bursts in an averaging module405. An interpolation is then made between the values of twoconsecutively calculated averages by the interpolation module 403.

FIG. 5 is an illustration of a data field for which three consecutivefading coefficient estimates are to be averaged and then interpolatingbetween consecutive averages. FIG. 5 shows two forward link slots 500,502. Each forward link slot 500, 502 has two pilot bursts 504, 506, 508,510. The fading coefficient for each pilot burst 504, 506, 508, 510 isestimated. A first average fading coefficient estimate c(k) iscalculated by taking the sum of the three estimates for the first threeconsecutive pilot bursts 504, 506, 508 and dividing by three. Next, asecond average fading coefficient c(k+1) is calculated for the threepilot bursts 506, 508, 510 by adding the fading coefficients for each ofthe pilot bursts 506, 508, 510 and dividing by three. A linearinterpolation is performed between the first and second average fadingcoefficients. To estimate the fading coefficient for a portion of datathat is a distance from the pilot burst 506, the following equation isused:

c(m)=(1−a)·c(k)+a·c(k+1), 0<a<1   (7)

The cross-correlation vector r_(yx) is calculated by repeating thisprocedure for each rake finger of each antenna.

Estimation of the Autocorrelation Matrix R_(yy)

The autocorrelation matrix of the received signal can be represented as:$\begin{matrix}{R_{yy} = {\frac{1}{M}{\sum\limits_{m = 1}^{M}{{y(m)}{y^{H}(m)}}}}} & (8)\end{matrix}$

where M is the number of samples used to perform the estimation andy(m)=[y₁₁(m), y₁₂(m), . . . y_(1N1)(m), y₂₁(m), y₂₂(m). . .y_(2N2)(m)]^(T) is the vector containing the received signal; y_(ij)(m)is the received signal at the i^(th) antenna and the j^(th) rakereceiver finger sampled at time mT after Walsh decover; N₁ is the numberof rake fingers associated with antenna 1 and N₂ is the number of rakefingers associated with antenna 2.

It can be seen from equation (8) that, in the case in which N₁=N₂ (i.e.,the same number of fingers are used to receive the incoming signal overeach of two antennas), R_(yy) is a 2N×2N matrix, comprising 2×2sub-matrices. Accordingly, the number of 2×2 sub-matrices is equal toN².

Those skilled in the art will recognize that the interference atdifferent rake fingers of each antenna is uncorrelated, due to thedifferences in the propagation delays of the signals received bydifferent rake fingers. Accordingly, the elements of the autocorrelationmatrix R_(yy) derived from rake fingers having different delays can beassumed to be zero. Only the estimation of 2×2 autocorrelation matricesof the signals of the rake fingers having the same delay (i.e., havingj₁=j₂) need be calculated: $R\begin{pmatrix}R^{(1)} & 0 & \cdots & \cdots & \cdots & \cdots & 0 \\0 & R^{(2)} & 0 & \cdots & \cdots & \cdots & \quad \\\vdots & \quad & ⋰ & \quad & \quad & \quad & \vdots \\\vdots & \quad & \quad & R^{(s)} & \quad & \quad & \vdots \\\vdots & \quad & \quad & \quad & ⋰ & \quad & \vdots \\\quad & \cdots & \cdots & \cdots & \cdots & ⋰ & \quad \\0 & \quad & \quad & \quad & \quad & 0 & R^{(N)}\end{pmatrix}$

In the presently disclosed method and apparatus using two antennas, each2×2 sub-matrix, R^((s)) located on the diagonal of the matrix R_(yy) (asshown above) can be expressed as follows: $R^{(s)} = {{\begin{pmatrix}{\frac{1}{M}{\sum\limits_{m = 1}^{M}{{y_{1s}(m)}}^{2}}} & {\frac{1}{M}{\sum\limits_{m = 1}^{M}{{y_{1s}(m)}{y_{2s}^{*}(m)}}}} \\{\frac{1}{M}{\sum\limits_{m = 1}^{M}{{y_{1s}^{*}(m)}{y_{2s}(m)}}}} & {\frac{1}{M}{\sum\limits_{m = 1}^{M}{{y_{2s}(m)}}^{2}}}\end{pmatrix}\quad 1} \leq s \leq N}$

wherein y_(1s)(m) is the signal at time mT received by the first antennathrough the s^(th) rake finger, and y_(2s)(m) is the signal at time mTreceived by the second antenna through the s^(th) rake finger. Each ofthe zeros shown above in the matrix R represents the assumed value of anoff-diagonal 2×2 sub-matrix.

In one presently disclosed methods and apparatus, the autocorrelationmatrix of the received signal is estimated by an R_(yy) estimationmodule 407 using the pilot bursts to estimate the value of R_(yy) in thedata chips. However, in an alternative method and apparatus, the R_(yy)estimation module uses the data chips directly, or both the pilot burstsand the data chips to determine the value of R_(yy) in the data chips.

In one presently disclosed method and apparatus in which pilot burstsare used to estimate R_(yy) in the data chips, an R_(yy) interpolationmodule 411 interpolates R_(yy) from the values determined in the pilotbursts. In an alternative method and apparatus, the R_(yy) estimationmodule 407 is coupled to an R_(yy) averaging module 409 that calculatesan average of two or three R_(yy) values determined in the pilot bursts.The averages output from the R_(yy) averaging module 409 are coupled tothe interpolation module 411 which interpolates the averages todetermine the value of R_(yy) in the data. The averaging andinterpolation performed by the averaging and interpolation modules 409,411 is essentially the same as the averaging and interpolation that isdone in the averaging and interpolation modules 405, 403.

Determination of the Optimum Combining Coefficients w

The optimum combining coefficients, w are determined by a combiningcoefficient evaluation module 415 using either equation (3), as providedabove. Once R_(yy) has been estimated by the R_(yy) estimation module407 and interpolated to represent R_(yy) in the data chips, the value ofR_(yy) is coupled to an inversion module 413 which inverts the matrixR_(yy). Equation (3) is then applied to determine the optimum combiningcoefficients.

In yet another alternative method and apparatus, R_(yy) is determinedfrom the pilot bursts. Equation (3) is used to determine the optimumcombiner coefficients in the pilot bursts. Then linear interpolation isused to determine the optimum combining coefficients in the data chips.

The computational complexity for the inversion required in equation (3)is very low due to the zeroing of all of the off-diagonal sub-matricesR^((s)) of the matrix R_(yy). That is, the inversion can be performedwithout inverting the entire matrix R_(yy). Rather, the sub-matricesR^((s)) can be separately inverted.

The algorithm described above is general and can be applied at a genericM×M autocorrelation matrix, where for the autocorrelation matrixinversion we can use the direct inversion or the well known recursiveleast square (RLS) algorithm.

Estimation of the Autocorrelation Matrix R_(nn)

FIG. 4B is a functional block diagram of a combiner coefficientprocessor 224′ of an alternative method and apparatus. As shown in FIG.4B, the combiner coefficient processor 224′ includes essentially thesame modules as the combiner coefficient processor 224 shown in FIG. 4A.However, the processor 224′ of FIG. 4B includes an R_(nn) estimationmodule 407′ which calculates an estimate of an autocorrelation matrix ofthe noise plus interference R_(nn)(m) instead of the R_(yy) estimationmodule 407 of FIG. 4A. To estimate the autocorrelation matrix of thenoise plus interference R_(nn)(m), the pilot bursts are preferably used.A first formula is represented as: $\begin{matrix}{R_{nn} = {\frac{1}{M}{\sum\limits_{m = 1}^{M}{{n(m)}{n^{H}(m)}}}}} & (9)\end{matrix}$

where n(m) is the estimated noise plus interference at the receiver in asample at time mT, and M is the number of samples used to perform theestimation (i.e. the number of symbols in the pilot burst). Eachcomponent of vector n(m) is determined by an R_(nn)(m) estimation module407′ by subtracting the channel gain c_(ij)(m) from the received pilotburst y_(ij)(m) as follows:

n _(ij)(m)=y _(pij)(m)−c _(ij)(m)   (10)

where y_(pij)(m) is the m^(th) sample of the received signal in thepilot burst at the j^(th) rake finger of the i^(th) antenna after Walshdecover and c_(ij)(m) is estimated by a fading coefficient estimationmodule 401′ using formula (6) provided above. The vector n(m) isgenerated by repeating this procedure for each rake finger of eachantenna 112, 114.

Alternatively, R_(nn) may be estimated by the following equation:$\begin{matrix}{R_{nn} = {\frac{1}{2M}{\sum\limits_{m = 1}^{M}{{n(m)}{n^{H}(m)}}}}} & (11)\end{matrix}$

where each component of vector n(m) is determined by the R_(nn)(m)estimation module 407′ using the formula:

n _(ij)(m)=y _(pij)(m)−y _(pij)(m+1)   (12)

where M is the number of samples used to perform the estimation (i.e.,the number of symbols in the pilot burst, less one).

According to equation (12), one pilot symbol of a rake finger of thefirst antenna 112 is subtracted from a next pilot symbol of the samerake finger of the same antenna 112. M is the number of samples used toperform the estimation, i.e. (the number of symbols in the pilot burst−1).

It should be noted that an alternative method for calculating R_(nn) is:

R _(nn) =R _(yy) −c·c ^(H)  (13)

where c·c^(H) is the dot product of the fading coefficient vector withthe transpose conjugate of the fading coefficient vector.

In one presently disclosed method and apparatus, the secondinterpolation module 411 interpolates the values of R_(nn) in the pilotto determine the value of R_(nn) in the data chips. Alternatively, theaverage module 409 averages a plurality of R_(nn) values determined fromthe pilot (i.e., two or three pilot values of R_(nn)). The average isthen coupled to the second interpolation module 411 which interpolatesthe averages to determine the value of R_(nn) in the data chips, asshown and described above with reference to FIG. 5. It should be notedthat with the exception of the processing that is done by the estimationmodules 407, 407′, and the processing done by the combining coefficientevaluation module 415, 415′, the functions of the combiner coefficientprocessors 224, 224′ are essentially identical.

In the presently disclosed method and apparatus shown in FIG. 4b, oncethe value of R_(nn) is determined in the data chips, the matrix R_(nn)is coupled to the inversion module 413. The inverted R_(nn) output fromthe inversion module 413 is coupled to the combining coefficientevaluation module 415′. Equation (4) is then applied by the combiningcoefficient evaluation module 415′ to determine the optimum combiningcoefficients w′.

Post Evaluation Interpolation

FIG. 6A is a functional block diagram of a combiner coefficientprocessor 600 of an alternative method and apparatus. As shown in FIG.6A, the combiner coefficient processor 600 includes essentially the samemodules as the combiner coefficient processor 224 shown in FIG. 4A.However, in the processor 600 of FIG. 6A, the interpolation is performedafter the evaluation of the optimum combining coefficients. Accordingly,the fading coefficient estimation module 401 is coupled directly to theevaluation module 415. Likewise, the R_(yy) estimation module 407 iscoupled directly to the martix inversion module 413. The evaluationmodule 415 is then coupled to an interpolation module 601 performs alinear interpolation between the values of w output from the evaluationmodule 415 in order to determine the values of w during the dataportions of each forward link slot.

Likewise, FIG. 6b is a functional block diagram of a combinercoefficient processor 600′ in yet another alternative method andapparatus. As shown in FIG. 6B, the combiner coefficient processor 600′includes essentially the same modules as the combiner coefficientprocessor 224′ shown in FIG. 4B. However, in the processor 600′ of FIG.6B, the interpolation is performed after the evaluation of the optimumcombining coefficients. Accordingly, the fading coefficient estimationmodule 401 is coupled directly to the evaluation module 415. Likewise,the R_(yy) estimation module 407′ is coupled directly to the martixinversion module 413. The evaluation module 415 is then coupled to aninterpolation module 601 perform a linear interpolation between thevalues of w′ output from the evaluation module 415 in order to determinethe values of w′ during the data portions of each forward link slot.

Estimation of the Signal-to-Interference-plus-Noise(SINR) Ratio

In one of the presently disclosed methods and apparatus, the values ofc_(ij)(m) and w_(ij)(m) from the combiner coefficient processor 224 arecoupled to an SINR evaluation module 228 (shown in FIG. 2B). In one ofthe presently disclosed methods and apparatus, a SNIR is calculated as:$\begin{matrix}{{SINR} = \frac{w^{H}c}{1 - {w^{H}c}}} & (14)\end{matrix}$

where w has been determined from equation (3) and c from equation (6).

In an alternative method and apparatus in which combiner coefficientprocessor 224′ is used to determine w′, the SINR is calculated as:

SINR=w′ ^(H) c  (15)

where c has been determined from (6).

In one of the presently disclosed methods and apparatus, SINR is used todetermine the rate at which data can be transmitted from the basestation 102 to the receiving station 110. As shown in FIGS. 2A and 2B,the combiner coefficient processor 224, 224′ is coupled to a SINRevaluation module 228 by signal lines 230, 231. Signal line 230 providesthe SINR evaluation module 228 with the value of either w or w′, ascalculated by the combiner coefficient processor 224, 224′. Signal line231 provides the SINR evaluation module 228 with the value forc_(ij)(m). The SINR evaluation module 228 determines the SINR inaccordance with either equation (14) or (15). The SINR evaluation module228 is coupled to a DRC module 232. The DRC module 232 determines therate at which data can be received from the base station 102, takinginto account the SINR of the signal being received from the base station102. This rate is then communicated to the base station.

Calculation of LLR

Most communication systems require the evaluation of the log likelihoodratios (LLR) of the coded bits in order to perform decoding at thereceiver (for example iterative or “turbo” decoding, conventionalViterbi decoding, etc.). One advantage of the presently disclosed methodand apparatus is that values of LLR can be easily computed from the softdecision values represented by either w or w′.

For example, assume that quadrature phase-shift keying (QPSK) or4-quadrature amplitude modulation (4-QAM) is used at the transmitter.Further, assume that d₀ and d₁ denote, respectively, the first and thesecond coded bit associated with the modulated symbol y_(d,ij), mappingcoded bit 0 at the input of the modulator to the modulation value +1 andcoded bit 1 at the input of the modulator to the modulation value −1 (asshown in FIG. 7). Then, the values of the LLR are computed using eitherequations (16) and (17) or equations (18) and (19):

LLR(d ₀ |y _(d)(m))=4·Re(w′(m)^(H) ·y _(d)(m))  (16)

LLR(d ₁ |y _(d)(m))=4·Im(w′(m)^(H) ·y _(d)(m))  (17)

LLR(d ₀ |y _(d)(m))=4·(1+h)·Re(w(m)^(H) ·y _(d)(m))  (18)

LLR(d ₁ |y _(d)(m))=4·(1+h)·Im(w(m)^(H) ·y _(d)(m))  (19)

where H denotes the transpose conjugate; Re(.) and Im(.) denotes realpart and imaginary part of a complex number, respectively;y_(d)(m)=[y_(d,11)(m),y_(d,12)(m), . . . y_(d,ij)(m), . . . ]^(T) is thevector containing the sampled received data signal at each rake finger213 associated with each antenna 112, 114 at time mT after Walshdecover; y_(d,ij) is the received data signal in the j^(th) rake finger213 coupled to the i^(th) antenna at time mT after Walsh decover;w(m)=[w₁₁(m),w₁₂(m), . . . w_(ij)(m). . . ]^(T) is the vector containingthe optimum combining coefficients at time mT evaluated using equation(3), w′(m)=[w′₁₁(m), w′₁₂(m), . . . w′_(ij)(m). . . ]^(T) is the vectorcontaining the optimum combining coefficients at time mT evaluated usingequation (4), and (1+h) has been defined in equation (5).

For BPSK signaling, only equations (16) or (18) are needed because theimaginary part is zero.

Accordingly, in one of the presently disclosed methods and apparatus,the error correcting decoder 226 performs the calculations shown inequations (16) and (17), or equations (18) and (19).

Industrial Application

Our disclosed method and apparatus is capable of exploitation inindustry and can be made and used whenever is it desired to do wirelessdata transfer. The individual components of the apparatus and methodshown herein, taken separate and apart from one another, may be entirelyconventional, it being their combination, which we claim as ourinvention.

While we have describe various modes of apparatus and method, the truespirit and scope of our invention is not limited thereto, but is limitedonly by the following claims and their equivalents, and we claim such asour invention.

What is claimed is:
 1. In a wireless communication receiver, the methodcomprising: receiving a plurality of signals at the receiver; samplingthe plurality of signals to generate sampled signals to the receiver;determining weights for the plurality of signals, comprising: estimatingan autocorrelation of the sampled signals; estimating a crosscorrelation between the sampled signals and corresponding transmittedsignals; and calculating the weights as a product of the autocorrelationand the cross correlation; receiving data signals at the receiver, thedata signals having corresponding transmitted data signals; and applyingthe weights to the data signals to generate an estimate of thetransmitted data signals.
 2. The method as in claim 1, wherein the crosscorrelation is a function of fading coefficients.
 3. The method as inclaim 1, further comprising: rotating the phase of the sampled signal.4. The method as in claim 1, wherein the plurality of signals receivedat the receiver includes information known a priori by the receiver. 5.The method as in claim 4, wherein the information corresponds to a pilotsequence.
 6. In a wireless communication receiver, the methodcomprising: receiving a plurality of signals at the receiver; samplingthe plurality of signals to generate sampled signals to the receiver;determining weights for the plurality of signals, comprising: estimatingan autocorrelation of the noise received at the receiver; estimating across correlation between the sampled signals and correspondingtransmitted signals; and calculating the weights as a product of theautocorrelation and the cross correlation; receiving data signals at thereceiver, the data signals having corresponding transmitted datasignals; and applying the weights to the data signals to generate anestimate of the transmitted data signals.
 7. The method as in claim 6,wherein the cross correlation is a function of fading coefficients. 8.The method as in claim 7, wherein the receiver includes a rake typereceiver having a plurality of fingers, further comprising: estimatingthe fading coefficients per each finger of the plurality of fingers ofthe rake type receiver.
 9. A wireless receiver apparatus, comprising:receiver means for processing a plurality of signal paths; samplingmeans for sampling a plurality of signals to generate sampled signals;weight calculation means for calculating weights for the plurality ofsignals, comprising: first estimation means for estimating anautocorrelation of the sampled signals; second estimation means forestimating a cross correlation between the sampled signals andcorresponding transmitted signals; and weight processing means forcalculating the weights as a product of the autocorrelation and thecross correlation; and weighting means for applying the weights to datasignals received at the apparatus and for generating an estimate ofcorresponding transmitted data signals.
 10. The wireless receiverapparatus of claim 9, wherein the first estimation means calculates theautocorrelation as${R_{yy} = {\frac{1}{M}{\sum\limits_{m = 1}^{M}{{y(m)}{y^{H}(m)}}}}},$

wherein y(m) is a sampled signal, and M is a total number of samples.11. The wireless receiver apparatus of claim 9, wherein the secondestimation means calculates the cross correlation as: r_(yx)=E [y(m)x*(m)]=c=[c₁₁(m),c₁₂(m), . . . ,c_(ij)(m). . . ]^(T), wherein E[ ] is anestimation operator, y(m) is a sampled signal, and x(m) is a transmittedsignal.